R Projects For Dummies

Joseph Schmuller, PhD, is a veteran of more than 25 years in Information Technology. He is the author of several books, including Statistical Analysis with R For Dummies and four editions of Statistical Analysis with Excel For Dummies. In addition, he has written numerous articles and created online coursework for Lynda.com.

Introduction 1 About This Book 2 Part 1: The Tools of the Trade 2 Part 2: Interacting with a User 2 Part 3: Machine Learning 2 Part 4: Large(ish) Data Sets 2 Part 5: Maps and Images 2 Part 6: The Part of Tens 3 What You Can Safely Skip 3 Foolish Assumptions 3 Icons Used in This Book 3 Beyond the Book 4 Where to Go from Here 4 Part 1: the Tools of the Trade 5 Chapter 1: R: What It Does and How It Does It 7 Getting R 7 Getting RStudio 8 A Session with R 11 The working directory 11 Getting started 12 R Functions 15 User-Defined Functions 16 Comments 18 R Structures 18 Vectors 18 Numerical vectors 19 Matrices 21 Lists 24 Data frames 25 Of for Loops and if Statements 28 Chapter 2: Working with Packages 31 Installing Packages 31 Examining Data 33 Heads and tails 33 Missing data 33 Subsets 34 R Formulas 35 More Packages 36 Exploring the tidyverse 37 Chapter 3: Getting Graphic 43 Touching Base 43 Histograms 44 Density plots 45 Bar plots 47 Grouping the bars 49 Quick Suggested Project 51 Pie graphs 53 Scatterplots 53 Scatterplot matrix 55 Box plots 56 Graduating to ggplot2 57 How it works 58 Histograms 59 Bar plots 61 Grouped bar plots 62 Grouping yet again 64 Scatterplots 67 The plot thickens 68 Scatterplot matrix 72 Box plots 73 Part 2: Interacting with a User 77 Chapter 4: Working with a Browser 79 Getting Your Shine On 79 Creating Your First shiny Project 80 The user interface 83 The server 84 Final steps 85 Getting reactive 86 Working with ggplot 89 Changing the server 90 A few more changes 92 Getting reactive with ggplot 94 Another shiny Project 96 The base R version 97 The ggplot version 104 Suggested Project 106 Chapter 5: Dashboards How Dashing! 107 The shinydashboard Package 107 Exploring Dashboard Layouts 108 Getting started with the user interface 109 Building the user interface: Boxes, boxes, boxes 110 Lining up in columns 117 A nice trick: Keeping tabs 121 Suggested project: Add statistics 125 Suggested project: Place valueBoxes in tabPanels 126 Working with the Sidebar 126 The user interface 128 The server 131 Suggested project: Relocate the slider 133 Interacting with Graphics 135 Clicks, double-clicks, and brushes oh, my! 135 Why bother with all this? 138 Suggested project: Experiment with airquality 141 Part 3: Machine Learning 143 Chapter 6: Tools and Data for Machine Learning Projects 145 The UCI (University of California-Irvine) ML Repository 146 Downloading a UCI dataset 146 Cleaning up the data 148 Exploring the data 150 Exploring relationships in the data 152 Introducing the Rattle package 157 Using Rattle with iris 159 Getting and (further) exploring the data 159 Finding clusters in the data 162 Chapter 7: Decisions, Decisions, Decisions 167 Decision Tree Components 167 Roots and leaves 168 Tree construction 168 Decision Trees in R 169 Growing the tree in R 169 Drawing the tree in R 171 Decision Trees in Rattle 173 Creating the tree 174 Drawing the tree 175 Evaluating the tree 176 Project: A More Complex Decision Tree 177 The data: Car evaluation 177 Data exploration 179 Building and drawing the tree 180 Evaluating the tree 181 Quick suggested project: Understanding the complexity parameter 181 Suggested Project: Titanic 182 Chapter 8: Into the Forest, Randomly 185 Growing a Random Forest 185 Random Forests in R 187 Building the forest 187 Evaluating the forest 189 A closer look 190 Plotting error 191 Plotting importance 193 Project: Identifying Glass 194 The data 194 Getting the data into Rattle 195 Exploring the data 196 Growing the random forest 198 Visualizing the results 198 Suggested Project: Identifying Mushrooms 200 Chapter 9: Support Your Local Vector 201 Some Data to Work With 201 Using a subset 202 Defining a boundary